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Tilapia is an important aquatic fish, but severe spoilage of tilapia is most likely related to the global aquaculture. The spoilage is mostly caused by specific spoilage organisms (SSO). Therefore, it is very important to use microbial models to predict the growth of SSO in tilapia. This study firstly verified Pseudomonas and Vibrio as the SSO of tilapia, then established microbial growth models based on Baranyi and chi-square automatic interaction detection (CHAID) models and compared their effectiveness. The results showed that both Baranyi model and CHAID model are appropriate for predicting the growth of microorganism. Baranyi model fits the microorganism growth better than CHAID model overall though CHAID model fits well at stationary phase. CHAID model predicts the microorganism growth accurately when the rate of change of the experiment data is big.
Key words: Specific spoilage organisms (SSO), tilapia, chi-square automatic interaction detection (CHAID), Baranyi, shelf-life.